This feature bounces inaudible ultrasound waves around your living space to check if anyone’s home. Someone who’s deaf or hard of hearing, for example, could receive a notification when their doorbell rings or when their dryer has finished a load of clothes.Īlong with Custom Sound Detection, Amazon plans to launch an Ultrasound Occupancy Routines feature for select Echo devices. Once you’ve taught Alexa to recognize this noise, you can use it to initiate a Routine that has Alexa send you a notification to close the door so your food doesn’t spoil.Īlexa users will find a ton of crazy complicated ways to use Custom Sound Detection, but we’re most interested in its potential as a simple accessibility tool. Take the sound your refrigerator door makes when it’s left open, for example. Next year, you’ll be able to teach Alexa to recognize sounds that are unique to your home and use these sounds to initiate more customized Routines. Once training is complete, you can program Alexa to respond to your custom sound with notifications or smart home actions. These samples go through an enrollment and training process in the cloud, although Amazon hasn’t told us how long this process takes. Coming next year, Custom Sound Detection lets you teach Alexa to identify new sounds to trigger notifications, routines, and other events.Ĭustomers can teach Alexa new sounds by providing 10 audio samples to an Echo device or the Alexa mobile app. Difficulties encountered include the kinds of noise that can be canceled and the time delay internal to the circuit.Amazon announced a boatload of new products during its September 2021 hardware event, and in all the excitement, many people overlooked Alexa’s new Custom Sound Detection feature. The software solution using adaptive filtering works better than the hardware solution but only with periodic noise. The hardware solution works well with periodic noise but has difficulty removing noise from non-periodic noise. The software portion of the experiment will use MATLAB to simulate the hardware circuit as well as simulate other methods: filtering unwanted signal, a pi phase shift for inverting the noise signal, the least mean squares algorithm, and the recursive least squares algorithm. The hardware will consist of building a noise cancelling circuit that uses headphones as an output, a microphone to pick up the noise to be cancelled and, if desired, a source sound. The objective of this project is to study the process of noise cancellation both as hardware and as software. The source sound may consist of speech, music played from a device such as an iPod or a computer, or no sound at all. Noise cancellation involves removing an unwanted noise while keeping the source sound.

Where is hardware and sound